The aim of this project is to integrate three types of information on the molecular pharmacology of cancer: (1) patterns of cancer cell inhibitory activity for compounds tested in the NCIs drug discovery program; (2) molecular structural features of the tested compounds; (3) possible molecular targets and modulators of activity in the cells used for testing -- as assessed through gene and protein expression profiling. The results have implications for drug discovery and design, for possible individualization of therapy, and for clinical studies of molecular markers on cancer cells. Analytical results to date have included the following: (i) Neural networks able to predict mechanism of drug action on the basis of patterns of activity in DTPs 60-cell line cancer drug screen; (ii) A program package (DISCOVERY) that integrates information on the chemical structure, activity, and possible molecular targets of compounds tested by NCI. As the name suggests, DISCOVERY was designed to search for novel mechanisms of action among the 60,000 compounds tested to date; (iii) Neural nets and statistical methods to predict (with only moderate sensitivity and specificity, it should be stressed) the clinical activity of phase II- evaluable drugs on the basis of patterns of activity in the screen; (iv) A program package MedMiner for fluent searching of the literature on genes, drugs, and diseases to aid in expression profiling studies; (v) QSAR studies and pharmacophore searches in the NCIs DIS database for new inhibitors of HIV-1 integrase and human topoisomerase ; (vi) creation of an interface with clinical tumor specimens in the Cancer Genome Anatomy Project.Experimental results to date have included (i) Development of a large protein expression database for the 60 cell lines in the NCI drug discovery program (by 2D-gel electrophoresis, in collaboration with Dr. Leigh Anderson, Large Scale Biology Corp.); (ii) generation of a 10,000-gene mRNA expression database for the 60 cell lines using cDNA microarrays (with collaborators at Stanford University and Synteni, Inc.); (iii) generation of a 42,000-gene mRNA expression database using Affymetrix oligonucleotide chips (with collaborators at the Whitehead Genome Center); (iv) Addition to that central database of experimental data on other cell types, including endothelial cells, multi-drug resistant cancer cells, p53-isogenic cell sets, and cell types used for HIV drug discovery; (v) Development of methods based on mass spectrometry to identify and characterize proteins in the gels in sub-picomole amounts. This project as a whole represents a collaboration with the NCI Developmental Therapeutics Program, as well as a number of other laboratories. Tools and data at http://discover.nci.nih.gov. - AIDS, Cancer, Drug Discovery, gel electrophoresis, gene expression, genetic algorithm, neural network, Protein expression, microarray,